
import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase_		      =	get_tests_dir('''fixtures/spiece.model''')




@require_sentencepiece
@require_tokenizers
class       __A(							_UpperCAmelCase							, unittest.TestCase					):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__            =     DebertaVaTokenizer
  SCREAMING_SNAKE_CASE__            =     DebertaVaTokenizerFast
  SCREAMING_SNAKE_CASE__            =     True
  SCREAMING_SNAKE_CASE__            =     True







  def 			UpperCAmelCase_   (self		):
       super().setUp()

       # We have a SentencePiece fixture for testing
       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     unk_token="""<unk>"""		)
       tokenizer.save_pretrained(self.tmpdirname		)







  def 			UpperCAmelCase_   (self			,     SCREAMING_SNAKE_CASE_		):
       UpperCamelCase__												=							"""this is a test"""
       UpperCamelCase__												=							"""this is a test"""
       return input_text, output_text







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""<pad>"""
       UpperCamelCase__												=							0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(__UpperCamelCase		)			,     __UpperCamelCase		)
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(__UpperCamelCase		)			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							list(self.get_tokenizer().get_vocab().keys()		)
       self.assertEqual(vocab_keys[0]			,     """<pad>"""		)
       self.assertEqual(vocab_keys[1]			,     """<unk>"""		)
       self.assertEqual(vocab_keys[-1]			,     """[PAD]"""		)
       self.assertEqual(len(__UpperCamelCase		)			,     3_00_01		)







  def 			UpperCAmelCase_   (self		):
       self.assertEqual(self.get_tokenizer().vocab_size			,     3_00_00		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							""" \tHeLLo!how  \n Are yoU?  """
       UpperCamelCase__												=							["""▁hello""", """!""", """how""", """▁are""", """▁you""", """?"""]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     do_lower_case=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     do_lower_case=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  @unittest.skip("""There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."""		)
  def 			UpperCAmelCase_   (self		):
       pass







  @unittest.skip("""There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."""		)
  def 			UpperCAmelCase_   (self		):
       pass







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""
       UpperCamelCase__												=							["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""
       UpperCamelCase__												=							["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""
       UpperCamelCase__												=							["""▁i""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """.""", ]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""
       UpperCamelCase__												=							["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """▁""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """▁""", """.""", ]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							""" \tHeLLo!how  \n Are yoU?  """
       UpperCamelCase__												=							["""▁""", """<unk>""", """e""", """<unk>""", """o""", """!""", """how""", """▁""", """<unk>""", """re""", """▁yo""", """<unk>""", """?"""]
       # fmt: on

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     do_lower_case=__UpperCamelCase			,     split_by_punct=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)

       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							self.get_tokenizer()
       UpperCamelCase__												=							self.get_rust_tokenizer()

       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""

       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							self.get_rust_tokenizer()
       UpperCamelCase__												=							tokenizer.encode(__UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.encode(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							"""This is a test"""
       UpperCamelCase__												=							[13, 1, 43_98, 25, 21, 12_89]
       UpperCamelCase__												=							["""▁""", """T""", """his""", """▁is""", """▁a""", """▁test"""]
       UpperCamelCase__												=							["""▁""", """<unk>""", """his""", """▁is""", """▁a""", """▁test"""]

       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase			,     keep_accents=__UpperCamelCase		)
       UpperCamelCase__												=							DebertaVaTokenizerFast(__UpperCamelCase			,     keep_accents=__UpperCamelCase		)

       UpperCamelCase__												=							tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.tokenize(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.tokenize(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       # fmt: off
       UpperCamelCase__												=							"""I was born in 92000, and this is falsé."""
       UpperCamelCase__												=							[13, 1, 23, 3_86, 19, 5_61, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]
       UpperCamelCase__												=							["""▁""", """I""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """é""", """.""", ]
       UpperCamelCase__												=							["""▁""", """<unk>""", """▁was""", """▁born""", """▁in""", """▁9""", """2000""", """,""", """▁and""", """▁this""", """▁is""", """▁fal""", """s""", """<unk>""", """.""", ]
       # fmt: on

       UpperCamelCase__												=							tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.tokenize(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.convert_ids_to_tokens(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)

       UpperCamelCase__												=							rust_tokenizer.encode(__UpperCamelCase			,     add_special_tokens=__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.tokenize(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)
       UpperCamelCase__												=							rust_tokenizer.convert_ids_to_tokens(__UpperCamelCase		)
       self.assertListEqual(__UpperCamelCase			,     __UpperCamelCase		)







  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							DebertaVaTokenizer(__UpperCamelCase		)

       UpperCamelCase__												=							tokenizer.encode("""sequence builders"""		)
       UpperCamelCase__												=							tokenizer.encode("""multi-sequence build"""		)

       UpperCamelCase__												=							tokenizer.build_inputs_with_special_tokens(__UpperCamelCase		)
       UpperCamelCase__												=							tokenizer.build_inputs_with_special_tokens(__UpperCamelCase			,     __UpperCamelCase		)

       self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]			,     __UpperCamelCase		)
       self.assertEqual(
           [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]			,     __UpperCamelCase			,     )







  @slow
  def 			UpperCAmelCase_   (self		):
       UpperCamelCase__												=							{"""input_ids""": [[1, 3_98_67, 36, 1_93_90, 4_86, 27, 3_50_52, 8_14_36, 18, 6_06_85, 12_25, 7, 3_50_52, 8_14_36, 18, 93_67, 1_68_99, 18, 1_59_37, 53, 5_94, 7_73, 18, 1_62_87, 3_04_65, 36, 1_59_37, 6, 4_11_39, 38, 3_69_79, 6_07_63, 1_91, 6, 3_41_32, 99, 6, 5_05_38, 3_90, 4_32_30, 6, 3_41_32, 27_79, 2_08_50, 14, 6_99, 10_72, 11_94, 36, 3_82, 1_09_01, 53, 7, 6_99, 10_72, 20_84, 36, 2_04_22, 6_30, 53, 19, 1_05, 30_49, 18_96, 10_53, 1_68_99, 15_06, 11, 3_79_78, 42_43, 7, 12_37, 3_18_69, 2_00, 1_65_66, 6_54, 6, 3_50_52, 8_14_36, 7, 5_56_30, 1_35_93, 4, 2], [1, 26, 1_50_11, 13, 6_67, 8, 10_53, 18, 2_36_11, 12_37, 7_23_56, 1_28_20, 34, 10_41_34, 12_09, 35, 1_33_13, 66_27, 21, 2_02, 3_47, 7, 1_64, 23_99, 11, 46, 44_85, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 12_32, 28_64, 1_57_85, 1_49_51, 1_05, 5, 85_81, 12_50, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=__UpperCamelCase			,     model_name="""microsoft/deberta-v2-xlarge"""			,     revision="""ad6e42c1532ddf3a15c39246b63f5559d558b670"""			,     )







"""simple docstring"""



import gc
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer

from diffusers import (
    AutoencoderKL,
    DDIMScheduler,
    StableDiffusionSAGPipeline,
    UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_IMAGE_PARAMS, TEXT_TO_IMAGE_PARAMS
from ..test_pipelines_common import PipelineLatentTesterMixin, PipelineTesterMixin


enable_full_determinism()




class 		a_    (			_UpperCAmelCase  ,    _UpperCAmelCase  ,    unittest.TestCase						):
    a   :					Dict			     =					StableDiffusionSAGPipeline
    a   :					Any			     =					TEXT_TO_IMAGE_PARAMS
    a   :					Optional[Any]			     =					TEXT_TO_IMAGE_BATCH_PARAMS
    a   :					Optional[int]			     =					TEXT_TO_IMAGE_IMAGE_PARAMS
    a   :					Optional[int]			     =					TEXT_TO_IMAGE_IMAGE_PARAMS
    a   :					Tuple			     =					False







    def   _snake_case       (      self      :							List[Any]  )		->Tuple:






        '''simple docstring'''






        torch.manual_seed(0  )
        _UpperCAmelCase        = UNetaDConditionModel(
            block_out_channels=(32, 64)  ,       layers_per_block=2  ,       sample_size=32  ,       in_channels=4  ,       out_channels=4  ,       down_block_types=("""DownBlock2D""", """CrossAttnDownBlock2D""")  ,       up_block_types=("""CrossAttnUpBlock2D""", """UpBlock2D""")  ,       cross_attention_dim=32  ,       )
        _UpperCAmelCase        = DDIMScheduler(
            beta_start=0.0_0_0_8_5  ,       beta_end=0.0_1_2  ,       beta_schedule="""scaled_linear"""  ,       clip_sample=__UpperCamelCase  ,       set_alpha_to_one=__UpperCamelCase  ,       )
        torch.manual_seed(0  )
        _UpperCAmelCase        = AutoencoderKL(
            block_out_channels=[32, 64]  ,       in_channels=3  ,       out_channels=3  ,       down_block_types=["""DownEncoderBlock2D""", """DownEncoderBlock2D"""]  ,       up_block_types=["""UpDecoderBlock2D""", """UpDecoderBlock2D"""]  ,       latent_channels=4  ,       )
        torch.manual_seed(0  )
        _UpperCAmelCase        = CLIPTextConfig(
            bos_token_id=0  ,       eos_token_id=2  ,       hidden_size=32  ,       intermediate_size=37  ,       layer_norm_eps=1e-05  ,       num_attention_heads=4  ,       num_hidden_layers=5  ,       pad_token_id=1  ,       vocab_size=10_00  ,       )
        _UpperCAmelCase        = CLIPTextModel(__UpperCamelCase  )
        _UpperCAmelCase        = CLIPTokenizer.from_pretrained("""hf-internal-testing/tiny-random-clip"""  )

        _UpperCAmelCase        = {
            """unet""": unet,
            """scheduler""": scheduler,
            """vae""": vae,
            """text_encoder""": text_encoder,
            """tokenizer""": tokenizer,
            """safety_checker""": None,
            """feature_extractor""": None,
        }
        return components







    def   _snake_case       (      self      :							Union[str, Any]  ,       __UpperCamelCase      :							Union[str, Any]  ,       __UpperCamelCase      :							Any=0  )		->Any:






        '''simple docstring'''






        if str(__UpperCamelCase  ).startswith("""mps"""  ):
            _UpperCAmelCase        = torch.manual_seed(__UpperCamelCase  )
        else:
            _UpperCAmelCase        = torch.Generator(device=__UpperCamelCase  ).manual_seed(__UpperCamelCase  )
        _UpperCAmelCase        = {
            """prompt""": """.""",
            """generator""": generator,
            """num_inference_steps""": 2,
            """guidance_scale""": 1.0,
            """sag_scale""": 1.0,
            """output_type""": """numpy""",
        }
        return inputs







    def   _snake_case       (      self      :							Optional[Any]  )		->Optional[int]:






        '''simple docstring'''






        super().test_inference_batch_single_identical(expected_max_diff=3e-3  )







@slow
@require_torch_gpu
class 		a_    (			unittest.TestCase						):







    def   _snake_case       (      self      :							Union[str, Any]  )		->str:






        '''simple docstring'''






        super().tearDown()
        gc.collect()
        torch.cuda.empty_cache()







    def   _snake_case       (      self      :							Tuple  )		->Union[str, Any]:






        '''simple docstring'''






        _UpperCAmelCase        = StableDiffusionSAGPipeline.from_pretrained("""CompVis/stable-diffusion-v1-4"""  )
        _UpperCAmelCase        = sag_pipe.to(__UpperCamelCase  )
        sag_pipe.set_progress_bar_config(disable=__UpperCamelCase  )

        _UpperCAmelCase        = """."""
        _UpperCAmelCase        = torch.manual_seed(0  )
        _UpperCAmelCase        = sag_pipe(
            [prompt]  ,       generator=__UpperCamelCase  ,       guidance_scale=7.5  ,       sag_scale=1.0  ,       num_inference_steps=20  ,       output_type="""np"""  )

        _UpperCAmelCase        = output.images

        _UpperCAmelCase        = image[0, -3:, -3:, -1]

        assert image.shape == (1, 5_12, 5_12, 3)
        _UpperCAmelCase        = np.array([0.1_5_6_8, 0.1_7_3_8, 0.1_6_9_5, 0.1_6_9_3, 0.1_5_0_7, 0.1_7_0_5, 0.1_5_4_7, 0.1_7_5_1, 0.1_9_4_9]  )

        assert np.abs(image_slice.flatten() - expected_slice  ).max() < 5e-2







    def   _snake_case       (      self      :							Union[str, Any]  )		->Tuple:






        '''simple docstring'''






        _UpperCAmelCase        = StableDiffusionSAGPipeline.from_pretrained("""stabilityai/stable-diffusion-2-1-base"""  )
        _UpperCAmelCase        = sag_pipe.to(__UpperCamelCase  )
        sag_pipe.set_progress_bar_config(disable=__UpperCamelCase  )

        _UpperCAmelCase        = """."""
        _UpperCAmelCase        = torch.manual_seed(0  )
        _UpperCAmelCase        = sag_pipe(
            [prompt]  ,       generator=__UpperCamelCase  ,       guidance_scale=7.5  ,       sag_scale=1.0  ,       num_inference_steps=20  ,       output_type="""np"""  )

        _UpperCAmelCase        = output.images

        _UpperCAmelCase        = image[0, -3:, -3:, -1]

        assert image.shape == (1, 5_12, 5_12, 3)
        _UpperCAmelCase        = np.array([0.3_4_5_9, 0.2_8_7_6, 0.2_5_3_7, 0.3_0_0_2, 0.2_6_7_1, 0.2_1_6_0, 0.3_0_2_6, 0.2_2_6_2, 0.2_3_7_1]  )

        assert np.abs(image_slice.flatten() - expected_slice  ).max() < 5e-2







    def   _snake_case       (      self      :							str  )		->str:






        '''simple docstring'''






        _UpperCAmelCase        = StableDiffusionSAGPipeline.from_pretrained("""stabilityai/stable-diffusion-2-1-base"""  )
        _UpperCAmelCase        = sag_pipe.to(__UpperCamelCase  )
        sag_pipe.set_progress_bar_config(disable=__UpperCamelCase  )

        _UpperCAmelCase        = """."""
        _UpperCAmelCase        = torch.manual_seed(0  )
        _UpperCAmelCase        = sag_pipe(
            [prompt]  ,       width=7_68  ,       height=5_12  ,       generator=__UpperCamelCase  ,       guidance_scale=7.5  ,       sag_scale=1.0  ,       num_inference_steps=20  ,       output_type="""np"""  ,       )

        _UpperCAmelCase        = output.images

        assert image.shape == (1, 5_12, 7_68, 3)